MBUS103 Global Managerial Economics

This case study is designed to assess students’ understanding of demand theory and application of the Excel functionalities. It is to introduce the steps and quantitative methods and tools to estimate demand function which is the primary objective of managerial economics. It will involve the estimation of demand using the graphical methodology and OLS regression methodology. It will be introduced how the estimated regression model will be used for forecasting future demand for the subject product.

**Case: **A coffee producer, The Turco Coffee intends to introduce a new 1 kg coffee grounds with a differentiated characteristic. And wishes to estimate the demand curve for the new coffee grounds. They have conducted a questionnaire survey of 1,462 people interviewed while they are shopping for a similar coffee grounds at different places in a month. Each people were asked whether they would actually purchase the coffee grounds at each price level represented to them. The price and quantity demanded relationship is classified by the answers of the people. The Excel spreadsheet, **Demand Model SS23.xlsx, **includes the demand schedule (cross-section data) collected by the consumer survey.

MBUS103 Global Managerial Economics

TASKS

- Identify the main determinant of demand for the introduced product – the new coffee grounds. Write the function of demand in the following form and explain the economically interpretable relationships.

*Q _{d} = f(X_{1}, X_{2}, X_{3}, X_{4},X_{5} )*

Analyze why and in which way the demand is affected by the determinants of demand for coffee grounds.

- Using the graphical method estimate (drive) the demand curve by plotting the price (P) and quantity demanded (Q
_{d}) using XY chart. Comment on the relationship between P and Q_{d}.

- Apply Regression analysis. To complete the modelling of the demand function, you hypothesize that the quantity demanded of coffee grounds (Q
_{d}) is a function of its price (P).

For this task you are required to utilise simple regression analysis which is to be conducted using cross section data provided with the file** Demand Model SS23.xlsx.**

MBUS103 Global Managerial Economics

The model has he following form:

*Q _{d} = *

*b*

_{0}*+*

*b*

_{1}*P + e*

_{i}* Where*:

*b**s*: are the intercept and estimated coefficient with the regression procedure.

*e _{i}*: is the error term

__Questions__

- Using economic theory, what are the hypothesised signs of the parameters, (
*b*_{0}*,**b*_{1}*)* - Estimate the regression equation using excel and write the estimated equation.
- Interpret the estimated
*b*coefficients for independent variables. - Compare your hypothesized signs (question 1) with your estimated sign. If there are any discrepancies, provide an appropriate explanation.
- Using the results from the regression analysis, are your estimated parameters statistically significant? Write null and alternative hypothesis and apply
*t*test procedure to justify the significance of the β coefficients and explain. - Estimate the confidence interval for
*b*_{1} - Write null and alternative hypothesis to apply
*F*test procedure to test the validity of the model you estimated and explain. - Interpret the estimated adj R
^{2} - Estimated regression model can be used to forecast the demand for the next period.

MBUS103 Global Managerial Economics

Assume that the expected value of the independent variable, the market price will be $35 for the next year.

Estimate the value of dependent variable, quantity demanded of new coffee grounds.

- Conclusion

Provide a brief summary of the procedures you applied, problems, limitations and other issues of estimating demand. Use APA referencing style.